In a wireless communication system, usually a transmitting end and a receiving end obtain higher transmission rate by using a spatial multiplexing mode and using a plurality of antennas. Compared with a common spatial multiplexing mode, an enhanced technique is that the receiving end feeds back channel information to the transmitting end and the transmitting end uses some transmission precoding techniques according to the obtained channel information to greatly improve transmission performance. For single-user Multi-input Multi-output (MIMO), channel characteristic vector information is directly used for precoding; and for Multi-user MIMO (MU-MIMO), more accurate channel information is needed.
In some techniques such as in Long Term Evolution LTE (Long Term Evolution) of 4G, 802.16m standard specification, feedback of channel information mainly utilizes a simpler single-codebook feedback way, but the performance of the transmission precoding technique of MIMO is more dependent on the accuracy of codebook feedback. Here, the basic principle of the channel information quantization feedback based on a codebook is simply introduced below:
Supposing that limited feedback channel capacity is B bps/Hz, the number of available code words is N=2B. Supposing that a characteristic vector space of a channel matrix H forms a codebook space ={F1, F2 L FN} after quantization, the transmitting end and the receiving end both save or generate the codebook (the codebook in the receiving end/transmitting end is the same) in real time. The receiving end selects a code word {circumflex over (F)} which is the most matched with a channel from the codebook space  in accordance with a certain criterion according to the received channel matrix H, and feeds back a code word sequence number i of the code word {circumflex over (F)} to the transmitting end, herein the code word sequence number is also called as a Precoding Matrix Indicator (PMI); and the transmitting end finds the corresponding precoding code word {circumflex over (F)} according to the fed-back code word sequence number i and thus obtains the channel information, herein {circumflex over (F)} denotes characteristic vector information of the channel.
With the high-speed development of the wireless communication technology, the wireless application of users is increasingly rich, thereby the quick increase of the wireless data service is driven, a huge challenge is brought to wireless access networks, and a multi-antenna technique is a key technique for coping with explosive increase challenge of wireless data service. At present, the multi-antenna technique supported in 4G is a horizontal-dimension beam forming technology which only supports 8 ports at most, and there is a greater potential to further greatly improve system capacity.
Evolution of the multi-antenna technique is performed mainly around targets such as higher beam forming/precoding gains, more space multiplexing layers (MU/SU), smaller interlayer interference, more overall coverage and smaller interference between sites. Massive MIMO and 3D MIMO are two main techniques for MIMO evolution in the next generation wireless communication.
For a system based on a Massive MIMO technique, a base station side is configured with a massive antenna array, for example, 100 antennas or even more. In this way, during data transmission, multiple users are multiplexed simultaneously at a same frequency by using the MU-MIMO technique, and generally, a ration of the number of the antennas and the number of multiplexed users is maintained to be about 5-10 times. In one aspect, no matter whether it is a strongly-correlative channel in a line-of-sight environment or a non-correlative channel under a rich scattering environment, a correlation coefficient between channels of any two users is exponentially attenuated with the increase of the number of the antennas. For example, when the base station side is configured with 100 antennas, the correlation coefficient between the channels of any two users is approximately 0, i.e., corresponding channels of multiple users are approximately orthogonal. In another aspect, a massive array can bring very considerable array gains and diversity gains. For 3D MIMO, in a vertical dimension and a horizontal dimension, beam forming capabilities are very good. This requires antennas to be arranged in 2D form instead of in a single dimension only. Due to the limitation of antenna size, there is little possibility to place more than a hundred of antennas in one dimension. Therefore, in most application scenarios, when the Massive MIMO technology is applied, the 3D MIMO is generally used in a combined manner. In addition, in order to reduce the antenna size and provide better diversity performance or multiplexing performance, dual-polarized antennas are also widely applied to the Massive MIMO. By using the dual-polarized antennas, the antenna size can be reduced to half of the original size.
For Massive MIMO, due to the introduction of massive antennas, the existing channel information feedback way is that, i.e., each antenna transmits a CSI-RS (Channel State Information Reference Signal), and a terminal detects the CSI-RS, obtains a channel matrix corresponding to each transmission resource through channel estimation, obtains an optimal precoding vector of each frequency-domain sub-band on a base band and optimal transmission layer number information of a broadband according to the channel matrix, and then performs a channel information feedback based on the introduced codebook feedback technique above-mentioned. The way of channel information feedback has greater problems during application in Massive MIMO. In one aspect, pilot overhead can increase with the increase of base station antenna number Nt and is very huge when the number of antennas is great. In another aspect, since the codebook used during feedback needs to contain a great many code words, it is very difficult to select the code words, and very great complexity is caused to the implementation at the terminal and there is almost no possibility to implement, or a huge cost needs to be spent. In addition, the overhead for codebook feedback is so great that the uplink overhead is huge. In other words, it is very difficult to obtain better performance in the massive antenna system by adopting the existing codebook feedback technique and expected multi-antenna gains cannot be obtained.
Especially, for dual-polarized channels, due to non-correlation in polarization, ranks of channels are generally greater than 1 and this means that more information needs to be fed back. More serious feedback performance and overhead problems than single-polarized channels would be encountered.